[Quant] [Bugfix] Fix quantization config matching with hf_to_vllm_mapper (#20046)

vllm/model_executor/model_loader/utils.py

@@ -24,6 +24,7 @@ from vllm.model_executor.models import ModelRegistry
 from vllm.model_executor.models.adapters import (as_classification_model,
                                                  as_embedding_model,
                                                  as_reward_model)
+from vllm.model_executor.models.interfaces import SupportsQuant
 from vllm.utils import is_pin_memory_available
 
 logger = init_logger(__name__)
@@ -294,13 +295,16 @@ def configure_quant_config(quant_config: QuantizationConfig,
 
     Note that model attributes are passed by reference to quant_config,
     enabling them to be updated by model_class.__new__ (ex. chatglm, qwen)
+
+    Once the `SupportsQuant` mixin has been added to all models, this
+    function can be removed
     """
-    packed_mapping = getattr(model_class, "packed_modules_mapping", None)
-    if packed_mapping is not None:
-        # pass packed_modules_mapping by reference to quant_config
-        quant_config.packed_modules_mapping = packed_mapping
-    else:
-        logger.warning(
-            "The model class %s has not defined `packed_modules_mapping`, "
-            "this may lead to incorrect mapping of quantized or ignored "
-            "modules", model_class.__name__)
+    if not issubclass(model_class, SupportsQuant):
+        hf_to_vllm_mapper = getattr(model_class, "hf_to_vllm_mapper", None)
+        packed_mapping = getattr(model_class, "packed_modules_mapping", None)
+
+        # pass mappings by reference to quant_config
+        if hf_to_vllm_mapper is not None:
+            quant_config.apply_vllm_mapper(hf_to_vllm_mapper)
+        if packed_mapping is not None:
+            quant_config.packed_modules_mapping = packed_mapping